For the comparisons with [1]} and its top performer model Ada-GVAE presented in Tables 1-4 in the main paper, we set the dimensionality \(d\)  of the latent space \(\mathcal {Z}\)  to 10, and the number of subspaces \(k\)  to 10. This puts us in a setting that is as close as possible to [1]}, where the latent space is 10-dimensional and the subspaces are 1-dimensional by construction. For all the quantitative experiments we trained 5 times the same model with different random seeds, and report the median results on each dataset. A summary of the hyperparameters are in Table REF .
